Warning
The information contained in this section is strictly for server implementors.
Applications which use the Client-Server API are generally unaffected by the
details contained here, and can safely ignore their presence.
The room state S’(E) after an event E is defined in terms of
the room state S(E) before E, and depends on whether
E is a state event or a message event:
- If E is a message event, then S’(E) = S(E).
- If E is a state event, then S’(E) is S(E), except
that its entry corresponding to E's event_type and state_key
is replaced by E's event_id.
The room state S(E) before E is the resolution of the set of
states {S’(E1), S’(E2), …} consisting of the states after each of
E's prev_events {E1, E2, …}, where the resolution of
a set of states is given in the algorithm below.
The state resolution algorithm for version 2 rooms uses the following
definitions, given the set of room states {S1, S2, …}:
- Power events
- A power event is a state event with type m.room.power_levels or
m.room.join_rules, or a state event with type m.room.member where the
membership is leave or ban and the sender does not match the
state_key. The idea behind this is that power events are events that might
remove someone's ability to do something in the room.
- Unconflicted state map and conflicted state set
- The unconflicted state map is the state where the value of each key exists
and is the same in each state Si. The conflicted state set is the
set of all other state events. Note that the unconflicted state map only has
one event per (event_type, state_key), whereas the conflicted state set
may have multiple events.
- Auth difference
- The auth difference is calculated by first calculating the full auth chain
for each state Si, that is the union of the auth chains for each
event in Si, and then taking every event that doesn't appear in
every auth chain. If Ci is the full auth chain of Si, then
the auth difference is ∪Ci − ∩Ci.
- Full conflicted set
- The full conflicted set is the union of the conflicted state set and the
auth difference.
- Reverse topological power ordering
The reverse topological power ordering of a set of events is the
lexicographically smallest topological ordering based on the DAG formed by
auth events. The reverse topological power ordering is ordered from earliest
event to latest. For comparing two topological orderings to determine which
is the lexicographically smallest, the following comparison relation on
events is used: for events x and y, x < y if
- x's sender has greater power level than y's sender,
when looking at their respective auth_events; or
- the senders have the same power level, but x's
origin_server_ts is less than y's origin_server_ts; or
- the senders have the same power level and the events have the same
origin_server_ts, but x's event_id is less than
y's event_id.
The reverse topological power ordering can be found by sorting the events
using Kahn's algorithm for topological sorting, and at each step selecting,
among all the candidate vertices, the smallest vertex using the above
comparison relation.
- Mainline ordering
Given an m.room.power_levels event P, the mainline of P
is the list of events generated by starting with P and recursively
taking the m.room.power_levels events from the auth_events, ordered
such that P is last. Given another event e, the closest
mainline event to e is the first event encountered in the mainline
when iteratively descending through the m.room.power_levels events in the
auth_events starting at e. If no mainline event is encountered
when iteratively descending through the m.room.power_levels events, then
the closest mainline event to e can be considered to be a dummy event
that is before any other event in the mainline of P for the purposes
of condition 1 below.
The mainline ordering based on P of a set of events is the
ordering, from smallest to largest, using the following comparison relation
on events: for events x and y, x < y if
- the closest mainline event to x appears before the closest
mainline event to y; or
- the closest mainline events are the same, but x's
origin_server_ts is less than y's origin_server_ts; or
- the closest mainline events are the same and the events have the same
origin_server_ts, but x's event_id is less than
y's event_id.
- Iterative auth checks
- The iterative auth checks algorithm takes as input an initial room state
and a sorted list of state events, and constructs a new room state by
iterating through the event list and applying the state event to the room
state if the state event is allowed by the authorization rules. If the
state event is not allowed by the authorization rules, then the event is
ignored. If a (event_type, state_key) key that is required for checking
the authorization rules is not present in the state, then the appropriate
state event from the event's auth_events is used if the auth event is
not rejected.
The resolution of a set of states is obtained as follows:
- Take all power events and any events in their auth chains, recursively,
that appear in the full conflicted set and order them by the reverse
topological power ordering.
- Apply the iterative auth checks algorithm, starting from the unconflicted state map,
to the list of events from the previous step to get a partially resolved
state.
- Take all remaining events that weren't picked in step 1 and order them by
the mainline ordering based on the power level in the partially resolved
state obtained in step 2.
- Apply the iterative auth checks algorithm on the partial resolved
state and the list of events from the previous step.
- Update the result by replacing any event with the event with the same key
from the unconflicted state map, if such an event exists, to get the final
resolved state.
Events that have been rejected due to failing auth based on the state at the
event (rather than based on their auth chain) are handled as usual by the
algorithm, unless otherwise specified.
Note that no events rejected due to failure to auth against their auth chain
should appear in the process, as they should not appear in state (the algorithm
only uses events that appear in either the state sets or in the auth chain of
the events in the state sets).
Rationale
This helps ensure that different servers' view of state is more likely to
converge, since rejection state of an event may be different. This can happen if
a third server gives an incorrect version of the state when a server joins a
room via it (either due to being faulty or malicious). Convergence of state is a
desirable property as it ensures that all users in the room have a (mostly)
consistent view of the state of the room. If the view of the state on different
servers diverges it can lead to bifurcation of the room due to e.g. servers
disagreeing on who is in the room.
Intuitively, using rejected events feels dangerous, however:
- Servers cannot arbitrarily make up state, since they still need to pass the
auth checks based on the event's auth chain (e.g. they can't grant themselves
power levels if they didn't have them before).
- For a previously rejected event to pass auth there must be a set of state
that allows said event. A malicious server could therefore produce a
fork where it claims the state is that particular set of state, duplicate the
rejected event to point to that fork, and send the event. The
duplicated event would then pass the auth checks. Ignoring rejected events
would therefore not eliminate any potential attack vectors.
Rejected auth events are deliberately excluded from use in the iterative auth
checks, as auth events aren't re-authed (although non-auth events are) during
the iterative auth checks.